Are you fascinated by cutting-edge additive manufacturing technologies, eager to develop a validated and predictive multi-domain computational model of this novel manufacturing process and motivated to cooperate with another PhD student who will develop the experimental setup and material models? Join us as a PhD candidate in a 2 PhD program and contribute to making volumetric 3D printing predictable, reliable, and industry-ready.
InformationAdditive manufacturing enables unprecedented design freedom, but today's technologies still struggle with predictability, efficiency, and material waste. A promising new approach, Tomographic Volumetric Additive Manufacturing (TVAM), can fabricate complex 3D objects in a single step without support structures. However, industrial adoption is currently limited by the lack of predictive process and material models.
As a PhD candidate, you will work on the M2i-funded research project "Multiphysics Modelling of Tomographic Volumetric Additive Manufacturing Processes for Predictive Product Properties (MTV)". Your research focuses on the development of an experimentally validated multi-domain computational model that describes the TVAM process and predicts the resulting product properties.
You will be embedded in the Mechanics of Materials section in the Department of Mechanical Engineering at Eindhoven University of Technology and closely collaborate with a second PhD candidate focusing on the development of the experimental manufacturing process setup and predictive material models, in the Processing & Performance section of the same department. The project is carried out together with the industrial partner Motion Imager and international academic collaborators.
Your main responsibilities include:
- Developing a robust, accurate and efficient multi-domain framework by coupling the optical, thermal, and mechanical domains, to describe the manufacturing process and predict the resulting product properties.
- Incorporating the physics-based constitutive material models that describe the liquid-to-solid transitions and viscoelastic behaviour under light exposure which are developed by the second PhD candidate.
- Experimental validation of the developed multi-domain solver by cooperation with the second PhD candidate and applying your solver to simple and complex geometries.
- Developing an uncertainty quantification and reduced order modelling approach to evaluate how variations in material properties and processing settings affect the product properties, in order to optimize the manufacturing process.
- Contributing to integrated demonstrations of predictive TVAM processes together with modelling and industrial partners.
- Publishing your results in leading scientific journals and presenting them at international conferences.
- Supervising MSc and BSc students and contributing to teaching activities.
Through your work, you will directly contribute to reducing material waste, enabling "first-time-right" manufacturing, and advancing digital twins for next-generation additive manufacturing.